This is a competing renewal application proposing ancillary studies to the NIDDK-Childhood Liver Disease Research and Education Network (ChiLDREN). Biliary atresia, the most common cause of neonatal cholestasis, results from a fibro-inflammatory obstruction of extrahepatic bile ducts. Despite nearly uniform progression to end-stage cirrhosis, the variable response to surgical/medical treatment and rate of progression of disease suggest the existence of unrecognized biological processes that are driving different phenotypes or stages of disease. In the first tenure of the award, we found evidence for dendritic and natural killer cells in pathogenic mechanisms of disease, identified a role for the ADD3 gene in susceptibility of disease, and generated a gene expression signature of inflammatory and fibrotic stages of liver disease at presentation, which have relationship to clinical outcome even when these stages are not present using standard histological criteria. In discovery-type preliminary studies for this application, we quantified inflammatory biomarkers in the serum and identified protein profiles that are highly specific for biliary atresia and predict adequate response to surgical treatment. These data form the foundation for the overall hypothesis that hepatic and circulating biomarkers linked to pathogenesis of biliary injury are predictors of diagnosis, stages of liver disease, and clinical outcome. To test this hypothesis, we will create a Data Integration Platform with key clinical, laboratory and histological data combined with comprehensive expression profiles for genes (in the liver) and protein (in the serum) of patients with biliary atresia and diseased- and healthy-controls. We will mine the platform to pursue three aims: 1) To define disease stages at diagnosis of biliary atresia with relevance to clinical outcome, 2) To identify biological predictors and favorable response to treatment, and 3) To discover serum biomarkers of tissue fibrosis and clinical end-points of cirrhosis. Experiments for Aim 1 will use RNAseq to generate whole-genome expression datasets to validate inflammatory and fibrotic signatures and stage the liver disease at diagnosis, identify molecular predictors of response to steroid treatment, and investigate new transcriptional mechanisms of disease. Experiments for Aims 2 and 3 will use protein-multiplexing technologies to quantify serum biomarkers of inflammation and fibrosis and highly stringent statistical models to define previously unrecognized subgroups of patients based on their biological makeup (stages of disease) that are predictive of response to standard surgery, new medical therapies, and progression of portal hypertension. By applying highly complementary approaches to study tissues from adequately sized cohorts that have been prospectively phenotyped by ChiLDREN, our experiments will provide insight into how future clinical trials and the care of affected children can be personalized based on biomarkers of disease.